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Titlebook: Introduction to Video and Image Processing; Building Real System Thomas B. Moeslund Textbook 2012 Springer-Verlag London Limited 2012 Image

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楼主: 可乐
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Neighborhood Processing,lied to investigate the relationship between neighboring pixels. For example, if a significant change in intensity value occurs this could indicate the boundary of an object and by finding the boundary pixels the object is located. In this (and the next) chapter a number of methods are presented whe
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BLOB Analysis, faced with the question of designing an algorithm that can find all the big coins in the image. The approach is to first binarize the image using a method from a previous chapter. Each object (coin) in the binary image is now defined as a group of connected white pixels, a so-called BLOB. This proc
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Tracking,ter introduces a framework for doing so, namely the so-called predict-match-update framework. First the notion of prediction is presented, which basically says something about where the object is expected to be in the future. For this purpose a motion model of the object is required. Different motio
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Geometric Transformations,wn are perhaps rotation and scaling, but others exist. In this chapter it is described how such transformations operate and the issues that need to be considered when doing such transformations are discussed. The term “geometric” transformation refers to the class of image transformation where the g
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Visual Effects,her words, just for the fun of it. This can be done in many different ways, where some are more interesting than others. In this chapter ten different methods for creating such visual effects are presented. The first five are based on manipulation of the actual pixel values and the last five on geom
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ally and cover basic concepts, relatively well established facts, lawlike and causal relations, theories, methods, standardized tests, biographic entries on significant figures, organizational profiles, indicat978-94-007-0753-5
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